The main inputs for the structural model were the structure maps of Upper Bahariya, Lower Bahariya, and Kharita Formations. These maps were used to manually generate fault sticks by drawing single polylines for upthrown and downthrown sides to represent the structural geometry. Fault pillars were generated to establish 3D grids and build models for the main horizons, which were divided into 34 zones to define a high-resolution stratigraphic framework.
Both the sediments deposited in the tidal-flat environment and the stacked sandstone units represent tidal deposits, indicating moderate to good reservoir quality. Percentage maps were generated for each zone taking the facies code into account and a variogram was created for each zone to determine the major direction, minor direction, and heading angle. A detailed understanding of the depositional environment’s anisotropy was the main input for the sequential high-resolution simulation of facies distributions.
In addition, a static geological model is provided by probability maps— showing a percentage for each facies code—and variogram maps, using FMI fullbore formation microimager and other log data, biostratigraphy data, core data, and petrophysical information.
Petrophysical model accurately identified porosity distribution
Using the Petrel platform and the Geostatistical Software Library (GSLIB), a stochastic petrophysical model was generated through sequential Gaussian simulation biased by facies distribution, which honors well data, petrophysical data transformation (porosity), variogram, and trends. Porosity is one of the most important petrophysical variables in hydrocarbon resource characterization because it describes the subsurface pore space available for fluid storage. Using GSLIB, the lithofacies model is often used to constrain the spatial distribution of porosity because in the hierarchy of subsurface heterogeneities, depositional facies govern the spatial and frequency characteristics of porosity to a large extent. Even though porosity can be quite variable within each facies, porosity statistics by facies generally exhibit less variation.
The porosity analysis can help the transition from qualitative description to quantitative analysis, bridge the gap between descriptive geology and quantitative modeling, and provide useful constraints to condition the facies model to be geologically realistic. Variogram analysis can help characterize the continuity of rock properties, including geological object size and anisotropy.
A broad hierarchical modeling workflow is an efficient way of modeling multiscale subsurface heterogeneities, including large-scale structural and stratigraphic heterogeneities, intermediate-scale facies heterogeneities, and smaller-scale petrophysical properties. The innovative workflow successfully captured the structural and stratigraphic heterogeneity of a very complicated channel system and provided a simulation grid validated for the dynamic phase of modeling.